Filters

Filters select which crashes count toward the numerator and how the exposure denominator is sized. Pass them as keyword args, a typed Selections model, or a dict (three ways), all validated locally. Each filter applies to one or more compute modes.

Discover, don't hard-code

Filter options and defaults can change as data is added. Fetch them at runtime with filters():

for f in hb.filters().modes["geofence"]:
    print(f.id, "→", [o.id for o in f.options], "default:", f.default)

This returns, per mode, every filter with its id, label, description, affects (n / d / both / rate), multiselect flag, valid options, and the default for that mode. The tables below are generated from the same source.

How affects reads

• n: changes the numerator (which crashes are counted).
• d: changes the denominator (the exposure miles).
• both: changes numerator and denominator together (e.g. vehicle class).
• rate: changes how the rate is derived from N and D (weighting / CI).

Multi-select filters accept either a single value or a list. Omitted fields fall back to the listed default.

Geofence filters

Filter	Type	Affects	Default	Options	Description
outcome	single-select	n	police_reported	police_reported: Police-reported observed_any_injury: Any reported injury airbag: Any airbag deployment ego_airbag: Ego airbag deployment ka: Serious+ (K or A) fatal: Fatal (K)	What kind of crash to count. Each outcome is a subset of police-reported.
severity	int	n	1	1: 1 2: 2 3: 3 4: 4 5: 5 6: 6 7: 7	Minimum CRIS vehicle-damage rating (1–7) a unit must have to be counted. Ignored for SF (SWITRS records no damage rating).
under_reporting	single-select	n	none	none: None (unadjusted) adjusted: Adjusted (Blincoe et al. 2023)	Apply Blincoe et al. 2023 NHTSA under-reporting multipliers (PDO ×2.48, non-fatal injury ×1.47, fatal ×1.0).
in_transport	single-select	n	in_transport	in_transport: In-transport only include_all: Include parked	Whether to exclude parked vehicles (Vehicle Parked Flag).
ego_vehicle	multi-select	both	cars, light_trucks	cars: Cars light_trucks: Light trucks heavy_trucks: Heavy trucks motorcycles: Motorcycles buses: Buses other: Other	Vehicle classes to count and to size the exposure denominator against.
unresolved_nfs	single-select	both	marginal	marginal: Use observed class share none: Exclude all: Include at full weight	How to treat units whose vehicle class could not be resolved (NFS tier 3).
road_type	multi-select	both	arterial, collector_local	interstate: Interstate other_freeway: Other freeway / expressway arterial: Arterial collector_local: Collector / local	Functional road classes to include. The dynamic operator multiplier only applies when every selected class is a surface street (arterial / collector_local).
robo_taxi_weighting	single-select	rate	county_wide	county_wide: County-wide operator_weighted: Operator-weighted (dynamic)	Plain county-wide Σ/Σ rate, or the Chen 2024 operator-weighted spatial multiplier (needs Waymo rider-only mileage).
multiplier_vmt	single-select	rate	calibrated	calibrated: Calibrated (TxDOT × VM-4) hpms: HPMS (Chen 2024)	Exposure source used inside the operator-weighted multiplier. Only relevant when robo_taxi_weighting=operator_weighted.
denominator_vmt	single-select	d	calibrated	calibrated: CPRD (Caltrans) hpms: HPMS (functional class)	Road-mileage dataset for the rate denominator. Effectively California-only: the CA pipelines expose a Caltrans CPRD vs HPMS toggle, whereas Texas/Arizona/Nevada counties have a single state-DOT calibrated denominator and reject 'hpms' with a 400.
weather	multi-select	both	dry, rain, fog	any: Any dry: Dry rain: Rain fog: Fog winter_storm: Winter storm	Weather buckets (NOAA-derived). 'any' disables the filter.
light_condition	multi-select	both	any	any: Any daylight: Daylight dawn_dusk: Dawn / dusk dark: Dark	Ambient-light buckets. 'any' disables the filter.
crash_year	int (multi)	n	2022	2022: 2022 2023: 2023 2024: 2024	Which year(s) of police-reported crash data feed the numerator. Geofence cities only (their units carry a crash_year column). Selecting multiple years pools their crashes and scales the denominator by the number of years, so the rate stays an annual mean. The listed years are advertised, not county-validated; years absent from a county are silently ignored.

Route filters

Filter	Type	Affects	Default	Options	Description
outcome	single-select	n	police_reported	police_reported: Police-reported observed_any_injury: Any reported injury airbag: Any airbag deployment ego_airbag: Ego airbag deployment ka: Serious+ (K or A) fatal: Fatal (K)	What kind of crash to count. Each outcome is a subset of police-reported.
severity	int	n	1	1: 1 2: 2 3: 3 4: 4 5: 5 6: 6 7: 7	Minimum CRIS vehicle-damage rating (1–7) a unit must have to be counted. Ignored for SF (SWITRS records no damage rating).
under_reporting	single-select	n	none	none: None (unadjusted) adjusted: Adjusted (Blincoe et al. 2023)	Apply Blincoe et al. 2023 NHTSA under-reporting multipliers (PDO ×2.48, non-fatal injury ×1.47, fatal ×1.0).
in_transport	single-select	n	in_transport	in_transport: In-transport only include_all: Include parked	Whether to exclude parked vehicles (Vehicle Parked Flag).
ego_vehicle	multi-select	both	combination	cars: Cars light_trucks: Light trucks combination: Combination trucks (Class 8 / tractor-trailer) motorcycles: Motorcycles buses: Buses other: Other	Vehicle classes to count and to size the exposure denominator against.
unresolved_nfs	single-select	both	marginal	marginal: Use observed class share none: Exclude all: Include at full weight	How to treat units whose vehicle class could not be resolved (NFS tier 3).
weather	multi-select	both	dry, rain, fog	any: Any dry: Dry rain: Rain fog: Fog winter_storm: Winter storm	Weather buckets (NOAA-derived). 'any' disables the filter.
light_condition	multi-select	both	any	any: Any daylight: Daylight dawn_dusk: Dawn / dusk dark: Dark	Ambient-light buckets. 'any' disables the filter.
driver_impairment	single-select	n	any	any: Any exclude_impaired: Exclude impaired impaired_only: Impaired only	Filter by driver-impairment coding. Route and depot modes only.
ci_method	single-select	rate	fay_feuer	fay_feuer: Fay-Feuer (weighted Poisson) empirical_bayes: Empirical Bayes (Gamma-Poisson)	Method for the 95% CI in route / depot modes.

Depot filters

Filter	Type	Affects	Default	Options	Description
outcome	single-select	n	police_reported	police_reported: Police-reported observed_any_injury: Any reported injury airbag: Any airbag deployment ego_airbag: Ego airbag deployment ka: Serious+ (K or A) fatal: Fatal (K)	What kind of crash to count. Each outcome is a subset of police-reported.
severity	int	n	1	1: 1 2: 2 3: 3 4: 4 5: 5 6: 6 7: 7	Minimum CRIS vehicle-damage rating (1–7) a unit must have to be counted. Ignored for SF (SWITRS records no damage rating).
under_reporting	single-select	n	none	none: None (unadjusted) adjusted: Adjusted (Blincoe et al. 2023)	Apply Blincoe et al. 2023 NHTSA under-reporting multipliers (PDO ×2.48, non-fatal injury ×1.47, fatal ×1.0).
in_transport	single-select	n	in_transport	in_transport: In-transport only include_all: Include parked	Whether to exclude parked vehicles (Vehicle Parked Flag).
ego_vehicle	multi-select	both	combination	cars: Cars light_trucks: Light trucks combination: Combination trucks (Class 8 / tractor-trailer) motorcycles: Motorcycles buses: Buses other: Other	Vehicle classes to count and to size the exposure denominator against.
unresolved_nfs	single-select	both	marginal	marginal: Use observed class share none: Exclude all: Include at full weight	How to treat units whose vehicle class could not be resolved (NFS tier 3).
weather	multi-select	both	dry, rain, fog	any: Any dry: Dry rain: Rain fog: Fog winter_storm: Winter storm	Weather buckets (NOAA-derived). 'any' disables the filter.
light_condition	multi-select	both	any	any: Any daylight: Daylight dawn_dusk: Dawn / dusk dark: Dark	Ambient-light buckets. 'any' disables the filter.
driver_impairment	single-select	n	any	any: Any exclude_impaired: Exclude impaired impaired_only: Impaired only	Filter by driver-impairment coding. Route and depot modes only.
ci_method	single-select	rate	empirical_bayes	fay_feuer: Fay-Feuer (weighted Poisson) empirical_bayes: Empirical Bayes (Gamma-Poisson)	Method for the 95% CI in route / depot modes.

Mode-specific vehicle classes

Route and depot modes count Class-8 combination trucks (combination) to match the combination-truck exposure denominator, so combination replaces heavy_trucks in those modes.